Generalization ability analysis.
Middlebury Stereo Datasets[1]} is a real-world dataset of stereo images along with ground truth disparity maps. We use this dataset to analyze the generalization ability of our method. To this end, we firstly let our models and DefocusNet [2]} be trained on FlyingThings3D [3]} with synthesized focal stacks by the rendering technique used in Barron et al. [4]}, and then test these models on Middlebury Stereo Datasets as well as the DefocusNet dataset. The quantitative results are shown in Table REF . One can see that both of our supervised and unsupervised (with AiF supervision) models achieve better generalization than DefocusNet on these two datasets.
